Cognitive biases in online and offline environments: A systematic review
DOI:
https://doi.org/10.33910/2686-9527-2026-8-1-39-56Keywords:
cognitive biases, cognitive errors, cyberspace, the internet, online environment, systematic literature reviewAbstract
Introduction. The perception of information is influenced by active digitalization, making it increasingly important to study thinking and factors affecting it. This systematic review examines the psychological study of cognitive biases (cognitive distortions) and aims to systematize accumulated knowledge about cognitive biases in offline and online environments.
Materials and Methods. The systematic literature review was conducted using electronic library systems: Google Scholar, E-library, PubMed, Ebsco. The articles in Russian and English were selected. The selection criteria were: type of research, full-text access, and a detailed description of the methodology and research results. The total corpus of articles consisted of 203 studies from 2002 to 2024, and 19 articles were selected for subsequent analysis.
Results. During a systematic analysis of selected articles, three areas of research were identified and described based on the relationship between cognitive biases and the following phenomena: personality traits, the nature of interpersonal interaction, and demographic characteristics. It was found that the presence of certain personality characteristics (e. g., anxiety, tendency to be lonely) is associated with specific types of biases, including catastrophizing and dichotomous thinking, regardless of the environment type. Interpersonal cognitive biases are interrelated with the manifestation of deviant behavior in online interaction. In both environments, there are special features in the manifestation of cognitive biases in individuals having different demographic characteristics.
Conclusion. Based on the systematic analysis, the following conclusions were drawn: (1) cognitive biases are multifactorial in nature, including personal, interpersonal, and demographic factors; (2) the type of environment is not a factor that determines the specifics of cognitive biases in individuals with different personality or demographic characteristics, while the interpersonal factor of cognitive biases requires further study. Promising areas of research include cross-cultural comparisons and the study of cognitive biases across different professional and age groups.
References
ЛИТЕРАТУРА
Батуев, Н. С. (2023) Когнитивные искажения в условиях информационного стресса. Труды молодых ученых Алтайского государственного университета, № 20, с. 147–150. EDN: BCRMSY
Башкатов, С. А., Шахов, А. А., Прудников, В. Б. (2022) Личностные особенности студентов, склонных к совершению ошибок, обусловленных иррациональными установками и когнитивными искажениями. Общество: социология, психология, педагогика, № 12 (104), с. 107–115. https://doi.org/10.24158/spp.2022.12.17
Беззубцева, М. В., Коробейникова, А. Н., Пашкова, И. Н. и др. (2023) Связь когнитивных искажений с факторами риска и хроническими неинфекционными заболеваниями у пользователей медицинских интернет-ресурсов. International Journal of Medicine and Psychology, т. 6, № 7, с. 114–123. EDN: BUQLAH
Бек, Дж. C. (2006) Когнитивная терапия: полное руководство. М.: Вильямс, 425 с.
Боброва, Л. А. (2021) Когнитивные искажения. Социальные и гуманитарные науки. Отечественная и зарубежная литература. Серия 3: Философия, № 2, c. 69–79. https://doi.org/10.31249/rphil/2021.02.04
Жихарева, Л. В., Лучинкина, И. С., Гребенюк, А. А., Лучинкина, А. И. (2022) Кибербуллинг как форма девиантного поведения личности в интернет-пространстве. Научный результат. Педагогика и психология образования, т. 8, № 4, c. 115–126. https://doi.org/10.18413/2313-8971-2022-8-4-0-9
Каменюкин, А. Г., Ковпак, Д. В. (2012) Стресс-менеджмент. 3-е изд. М.; СПб.: Питер, 206 с.
Крюкова, Т. Л., Екимчик, О. А., Хохлова, Ю. А., Кирпичник, О. В. (2018) Феномен когнитивных искажений субъективных оценок жизненных явлений и его измерение (первичная русскоязычная адаптация шкалы когнитивных искажений — CdS). Вестник Костромского государственного университета. Серия: Педагогика. Психология. Социокинетика, № 4, с. 61–67. EDN: YVSQZN
Левкова, Т. В. (2020) Подготовка будущих психологов: трудности и перспективы. Мир науки, культуры, образования, № 2 (81), с. 158–161. EDN: ZEHHYE
Легостаева, Е. С. (2018) Методологические предпосылки исследования когнитивных ошибок. В кн.: С. П. Акутина (ред.). Современная наука в теории и практике. Ч. IV. М.: Перо, с. 53–72.
Лучинкина, И. С. (2018) Особенности коммуникативного поведения личности в интернет-пространстве. Ученые записки Крымского инженерно-педагогического университета. Серия: Педагогика. Психология, № 4, с. 92–98. EDN: QESKQS
Лучинкина, И. С. (2023a) Психологические особенности личности с различными уровнями морально- этической ответственности. Человеческий капитал, № 3 (171), с. 131–140. https://doi.org/10.25629/HC.2023.03.13
Лучинкина, И. С. (2023b) Когнитивные детерминанты цифрового поведения личности. Гуманитарные науки, № 2 (62), с. 134–142. EDN: LKRQZX
Лучинкина, И. С., Коршак, А. А. (2023) Когнитивные особенности интернет-активной личности. Ученые записки Крымского федерального университета имени В. И. Вернадского. Социология. Педагогика. Психология, т. 9 (75), № 4, с. 128–135. EDN: LIXTKJ
Лучинкина, И. С., Фазилова, А. Э. (2024) Психологические особенности жертв и инициаторов, включённых в буллинг-структуру. Вестник Государственного университета просвещения. Серия: Психологические науки, № 3, с. 21–35. https://doi.org/10.18384/2949-5105-2024-3-21-35
Микляева, А. В., Безгодова, С. А. (2017) «Клиповое мышление» в структуре стилевых характеристик познавательной деятельности студентов. Ярославский педагогический вестник, № 5, с. 223–227. EDN: ZSNKNP
Опекина, Т. П. (2020) Когнитивные предикторы психологического благополучия и удовлетворенности жизнью мужчин-курсантов военных вузов. Вестник Костромского государственного университета. Серия: Педагогика. Психология. Социокинетика, т. 26, № 3, с. 54–61. EDN: DWTMTH
Орёл, В. Е., Сенин, И. Г. (2008) Опыт адаптации зарубежного опросника: организационный и содержательный аспект. Вестник Южно-Уральского государственного университета. Серия: Психология, № 33 (133), с. 71–77. EDN: KXJHWN
Павлова, Т. С., Банников, Г. С. (2013) Современные теории суицидального поведения подростков и молодежи. Психологическая наука и образование, № 4, с. 59–69. EDN: RSRAGV
Швец, Ю. Ю. (2024) Когнитивные искажения и проблемное использование интернета у студентов: педагогические меры профилактики. Мир науки. Педагогика и психология, т. 12, № 3, статья 107. EDN: EZJEAR
Щелин, И. В., Петроченко, И. А. (2024) Когнитивная, поведенческая и эмоциональная составляющие коммуникативного поведения подростков в информационном пространстве. Сибирский психологический журнал, № 91, с. 81–98. https://doi.org/10.17223/17267080/91/5
Başbuğ, S., Cesur, G., Durak Batıgün, A. (2017) Perceived parental styles and adult separation anxiety: The mediating role of interpersonal cognitive distortions. Turkish Journal of Psychiatry, vol. 28, no. 4, pp. 255–267.
Batmaz, S., Kocbiyik, S., Yalçınkaya-Alkar, Ö., Turkcapar, M. H. (2016) Cognitive distortions mediate the relationship between defense styles and depression in female outpatients. The European Journal of Psychiatry, vol. 30, no. 4. [Online]. Available at: https://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S0213-61632016000400002 (accessed 14.06.2025).
Benhalilem, A., Hartani, A. (2024) Cognitive distortions among university students in light of some variables. Psychology and Education Journal, vol. 61, no. 3, pp. 684–698.
Fitri, R. A., Anggita, S. J. (2015) Loneliness and cognitive distortion in adolescent Facebookers. Anima, Indonesian Psychological Journal, vol. 30, no. 3, pp. 155–162. https://doi.org/10.24123/aipj.v30i3.545
Guess, A. M., Lerner, M., Lyons, B. et al. (2020) A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 27, pp. 15536–15545. https://doi.org/10.1073/pnas.1920498117
Hosseinmardi, H., Ghasemian, A., Rivera-Lanas, M. et al. (2024) Causally estimating the effect of YouTube’s recommender system using counterfactual bots. Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 8, article e2313377121. https://doi.org/10.1073/pnas.2313377121
Kouros, T., Theodosiou, Z., Themistocleous, C. (2025) Machine learning bias: Genealogy, expression and prevention. In: P. A. Christou (ed.). Artificial Intelligence (AI) in Social Research. Oxfordshire; Boston: CABI Books Publ., pp. 113–126. https://doi.org/10.1079/9781800626607.0011
Kozyreva, A., Lewandowsky, S., Hertwig, R. (2020) Citizens versus the Internet: Confronting digital challenges with cognitive tools. Psychological Science in the Public Interest, vol. 21, no. 3, pp. 103–156. https://doi.org/10.1177/1529100620946707
Kuzucu, Y., Ertürk, Ö. S., Şimşek, Ö. F., Gökdaş, İ. (2020) Cognitive distortions and problematic Internet use connection: Examining the mediator roles of loneliness and social anxiety by partialling out the effects of social desirability. Journal of Evidence-Based Psychotherapies, vol. 20, no. 1, pp. 51–76. https://doi.org/10.24193/jebp.2020.1.4
Mirhoseini, M., Early, S., Hassanein, K. (2022) All eyes on misinformation and social media consumption: A pupil dilation study. Information Systems and Neuroscience (NeuroIS 2022), vol. 58, pp. 73–80. https://doi.org/10.1007/978-3-031-13064-9_7
Roganović, J. (2024) Familiarity with ChatGPT features modifies expectations and learning outcomes of dental students. International Dental Journal, vol. 74, no. 6, pp. 1456–1462. https://doi.org/10.1016/j.identj.2024.04.012
Sánchez-Fernández, M., Borda-Mas, M., Horvath, Z., Demetrovics, Z. (2024) Similarities and differences in the psychological factors associated with generalised problematic internet use, problematic social media use, and problematic online gaming. Comprehensive Psychiatry, vol. 134, article 152512. https://doi.org/10.1016/j.comppsych.2024.152512
Shi, C., Du, X., Chen, W., Ren, Z. (2024) Predictive roles of cognitive biases in health anxiety: A machine learning approach. Stress and Health, vol. 40, no. 5, article e3463. https://doi.org/10.1002/smi.3463
Şimşek, O. M., Koçak, O., Younis, M. Z. (2021) The impact of interpersonal cognitive distortions on satisfaction with life and the mediating role of loneliness. Sustainability, vol. 13, no. 16, article 9293. https://doi.org/10.3390/su13169293
Talboy, A. N., Fuller, E. (2023) Challenging the appearance of machine intelligence: Cognitive bias in LLMs and best practices for adoption. arXiv, [Online]. Available at: https://doi.org/10.48550/arXiv.2304.01358 (accessed 14.06.2025).
Zhang, J., Song, W., Liu, Y. (2025) Cognitive bias in generative AI influences religious education. Scientific Reports, vol. 15, article 15720. https://doi.org/10.1038/s41598-025-99121-6
REFERENCES
Başbuğ, S., Cesur, G., Durak Batıgün, A. (2017) Perceived parental styles and adult separation anxiety: The mediating role of interpersonal cognitive distortions. Turkish Journal of Psychiatry, vol. 28, no. 4, pp. 255–267. (In English)
Bashkatov, S. A., Shakhov, A. A., Prudnikov, V. B. (2022) Personality traits of students prone to making errors due to irrational attitudes and cognitive distortions. Society: Sociology, Psychology, Pedagogics, no. 12 (104), pp. 107–115. https://doi.org/10.24158/spp.2022.12.17 (In Russian)
Batmaz, S., Kocbiyik, S., Yalçınkaya-Alkar, Ö., Turkcapar, M. H. (2016) Cognitive distortions mediate the relationship between defense styles and depression in female outpatients. The European Journal of Psychiatry, vol. 30, no. 4. [Online]. Available at: https://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S0213-61632016000400002 (accessed 14.06.2025). (In English)
Batuev, N. S. (2023) Cognitive distortions under informational stress. Trudy molodykh uchenykh Altajskogo gosudarstvennogo universiteta, no. 20, pp. 147–150. (In Russian)
Beck, J. S. (2006) Cognitive therapy: a complete guide. Moscow: Vil’yams Publ., 425 p. (In Russian)
Benhalilem, A., Hartani, A. (2024) Cognitive distortions among university students in light of some variables. Psychology and Education Journal, vol. 61, no. 3, pp. 684–698. (In English)
Bezzubtseva, M. V., Korobejnikova, A. N., Pashkova, I. N. et al. (2023) The relationship of cognitive distortions with risk factors and chronic non-communicable diseases in users of medical Internet resources. International Journal of Medicine and Psychology, vol. 6, no. 7, pp. 114–123. (In Russian)
Bobrova, L. A. (2021) Cognitive biases. Social Sciences and Humanities. Domestic and Foreign Literature. Series 3: Philosophy, no. 2, pp. 69–79. https://doi.org/10.31249/rphil/2021.02.04 (In Russian)
Fitri, R. A., Anggita, S. J. (2015) Loneliness and cognitive distortion in adolescent Facebookers. Anima, Indonesian Psychological Journal, vol. 30, no. 3, pp. 155–162. https://doi.org/10.24123/aipj.v30i3.545 (In English)
Guess, A. M., Lerner, M., Lyons, B. et al. (2020) A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 27, pp. 15536–15545. https://doi.org/10.1073/pnas.1920498117 (In English)
Hosseinmardi, H., Ghasemian, A., Rivera-Lanas, M. et al. (2024) Causally estimating the effect of YouTube’s recommender system using counterfactual bots. Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 8, article e2313377121. https://doi.org/10.1073/pnas.2313377121 (In English)
Kamenyukin, A. G., Kovpak, D. V. (2012) Stress management. 3rd ed. Moscow; Saint Petersburg: Piter Publ., 206 p. (In Russian)
Kouros, T., Theodosiou, Z., Themistocleous, C. (2025) Machine learning bias: Genealogy, expression and prevention. In: P. A. Christou (ed.). Artificial Intelligence (AI) in Social Research. Oxfordshire; Boston: CABI Books Publ., pp. 113–126. https://doi.org/10.1079/9781800626607.0011 (In English)
Kozyreva, A., Lewandowsky, S., Hertwig, R. (2020) Citizens versus the Internet: Confronting digital challenges with cognitive tools. Psychological Science in the Public Interest, vol. 21, no. 3, pp. 103–156. https://doi.org/10.1177/1529100620946707 (In English)
Kryukova, T. L., Ekimchik, O. A., Khokhlova, Yu. A., Kirpichnik, O. V. (2018) Cognitive distortions phenomenon in the evaluation of well-being (a primary Russian adaptation of cognitive distortions scale — CDS). Vestnik of Kostroma State University. Series: Pedagogy. Psychology. Sociokinetics, no. 4, pp. 61–67. (In Russian)
Kuzucu, Y., Ertürk, Ö. S., Şimşek, Ö. F., Gökdaş, İ. (2020) Cognitive distortions and problematic Internet use connection: Examining the mediator roles of loneliness and social anxiety by partialling out the effects of social desirability. Journal of Evidence-Based Psychotherapies, vol. 20, no. 1, pp. 51–76. https://doi.org/10.24193/jebp.2020.1.4 (In English)
Legostaeva, E. S. (2018) Methodological prerequisites for studying cognitive errors. In: S. P. Akutina (ed.). Modern science in theory and practice. Pt. IV. Moscow: Pero Publ., pp. 53–72. (In Russian)
Levkova, T. V. (2020) Training for future psychologists: Difficulties and prospects. Mir nauki, kul’tury, obrazovaniya, no. 2 (81), pp. 158–161. (In Russian)
Luchinkina, I. S. (2018) Features of communicative behavior of personality in the Internet space. Uchenye zapiski Krymskogo inzhenerno-pedagogicheskogo universiteta. Serija: Pedagogika. Psikhologiya, no. 4 (14), pp. 92–98. (In Russian)
Luchinkina, I. S. (2023a) Psychological characteristics of a person with different levels of moral and ethical responsibility. Human capital, no. 3 (171), pp. 131–140. https://doi.org/10.25629/HC.2023.03.13 (In Russian)
Luchinkina, I. S. (2023b) Cognitive determinants of personal digital behavior]. The Humanities, no. 2 (62), pp. 134–142. (In Russian)
Luchinkina, I. S., Korshak, A. A. (2023) Cognitive features of an internet-active personality. Scientific Notes of V. I. Vernadsky Crimean Federal University. Sociology. Pedagogy. Psychology, vol. 9 (75), no 4, pp. 128–135. (In Russian)
Luchinkina, I. S., Fazilova, A. E. (2024) Psychological features of victims and initiators included in the bullying structure. Bulletin of State University of Education. Series: Psychological Sciences, no. 3, pp. 21–35. https://doi.org/10.18384/2949-5105-2024-3-21-35 (In Russian)
Miklyaeva, A. V., Bezgodova, S. A. (2017) “Clip mind” in the structure of the style characteristics in students’ cognitive activity. Yaroslavl Pedagogical Bulletin, no. 5, pp. 223–227. (In Russian)
Mirhoseini, M., Early, S., Hassanein, K. (2022) All eyes on misinformation and social media consumption: A pupil dilation study. Information Systems and Neuroscience (NeuroIS 2022), vol. 58, pp. 73–80. https://doi.org/10.1007/978-3-031-13064-9_7 (In English)
Opekina, T. P. (2020) Cognitive predictors of psychological well-being and satisfaction with the life of male students at military higher education institutions. Vestnik of Kostroma State University. Series: Pedagogy. Psychology. Sociokinetics, vol. 26, no 3, pp. 54–61. (In Russian)
Orjol, V. E., Senin, I. G. (2008) The experience of adapting a foreign questionnaire: Organizational and content aspect. Bulletin of the South Ural State University. Series “Psychology”, no. 33 (133), pp. 71–77. (In Russian)
Pavlova, T. S., Bannikov, G. S. (2013) Modern theories of suicidal behavior in adolescents and young people. Psychological Science and Education, no. 4, pp. 59–69. (In Russian)
Roganović, J. (2024) Familiarity with ChatGPT features modifies expectations and learning outcomes of dental students. International Dental Journal, vol. 74, no. 6, pp. 1456–1462. https://doi.org/10.1016/j.identj.2024.04.012 (In English)
Sánchez-Fernández, M., Borda-Mas, M., Horvath, Z., Demetrovics, Z. (2024) Similarities and differences in the psychological factors associated with generalised problematic internet use, problematic social media use, and problematic online gaming. Comprehensive Psychiatry, vol. 134, article 152512. https://doi.org/10.1016/j.comppsych.2024.152512 (In English)
Shchelin, I. V., Petrochenko, I. A. (2024) Cognitive, behavioural and emotional components of adolescents’ communicative behaviour in information space. Siberian Journal of Psychology, no. 91, pp. 81–98. https://doi.org/10.17223/17267080/91/5 (In Russian)
Shi, C., Du, X., Chen, W., Ren, Z. (2024) Predictive roles of cognitive biases in health anxiety: A machine learning approach. Stress and Health, vol. 40, no. 5, article e3463. https://doi.org/10.1002/smi.3463 (In English)
Shvets, Yu. Yu. (2024) Cognitive distortions and problematic use of the internet in students: pedagogical prevention measures. World of Science. Pedagogy and psychology, vol. 12, no. 3, article 107. (In Russian)
Şimşek, O. M., Koçak, O., Younis, M. Z. (2021) The impact of interpersonal cognitive distortions on satisfaction with life and the mediating role of loneliness. Sustainability, vol. 13, no. 16, article 9293. https://doi.org/10.3390/su13169293 (In English)
Talboy, A. N., Fuller, E. (2023) Challenging the appearance of machine intelligence: Cognitive bias in LLMs and best practices for adoption. arXiv, [Online]. Available at: https://doi.org/10.48550/arXiv.2304.01358 (accessed 14.06.2025). (In English)
Zhang, J., Song, W., Liu, Y. (2025) Cognitive bias in generative AI influences religious education. Scientific Reports, vol. 15, article 15720. https://doi.org/10.1038/s41598-025-99121-6 (In English)
Zhikhareva, L. V., Luchinkina, I. S., Grebenyuk, A. A., Luchinkina, A. I. (2022) Deviant behavior on the Web: Cyberbullying. Research Result. Pedagogy and Psychology of Education, vol. 8, no. 4, pp. 115–126 https://doi.org/10.18413/2313-8971-2022-8-4-0-9 (In Russian)
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Copyright (c) 2026 Vlada V. Sokolovskaya, Sofia S. Krokoleva, Oleg M. Samoilov, Evgeniya S. Savelyeva, Liliya O. Beloglazova, Albina V. Boiko, Anastasiya S. Rudich
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